* [http://hltfbk.github.io/Excitement-Open-Platform/ EXCITEMENT Open Platform (EOP)] - A generic multi-lingual platform for textual inference made available to the scientific and technological communities by the [http://www.excitement-project.eu/ EU project EXCITEMENT]

* [http://www.investigacion.frc.utn.edu.ar/mslabs/~jcastillo/Sagan-test-suite/ RTE-3-Expanded, RTE-4-Expanded, RTE-5-Expanded.] RTE data set expanded in the two and three way task, at least 2000 pairs in each data set.

* [http://www.investigacion.frc.utn.edu.ar/mslabs/~jcastillo/Sagan-test-suite/ RTE-3-Expanded, RTE-4-Expanded, RTE-5-Expanded.] RTE data set expanded in the two and three way task, at least 2000 pairs in each data set.

* [http://art.uniroma2.it/zanzotto/resources/WIKI_FINAL_CORPUS_v1.zip Wiki Entailment Corpus] A RTE-like set of entailment pairs extracted from Wikipedia revisions described in [http://aclweb.org/anthology/W/W10/W10-3504.pdf this paper]

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* [https://github.com/daoudclarke/rte-experiment The Guardian Headlines Entailment Training Dataset] An automatically generated dataset of 32,000 pairs similar to the RTE-1 dataset.

* a [[RTE Knowledge Resources#Call for Resources|call for resources]], inviting system developers to share the resources used by their own TE engines, to both help improve the TE technology and further test and evaluate such resources;

* a [[RTE Knowledge Resources#Call for Resources|call for resources]], inviting system developers to share the resources used by their own TE engines, to both help improve the TE technology and further test and evaluate such resources;

* [[RTE Knowledge Resources#Ablation tests|the ablation tests]] carried out in the RTE challenges in order to evaluate the impact of knowledge resources and tools on TE system performances;

* [[RTE Knowledge Resources#Ablation tests|the ablation tests]] carried out in the RTE challenges in order to evaluate the impact of knowledge resources and tools on TE system performances;

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* [[RTE Knowledge Resources#Publicly available Resources|lists of knowledge resources]], both publically available and unpublished, used by systems participating in the last RTE challenges.

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* [[RTE Knowledge Resources#Publicly available Resources|lists of knowledge resources]], both publicly available and unpublished, used by systems participating in the last RTE challenges.

Revision as of 04:14, 9 December 2013

Textual entailment systems rely on many different types of NLP resources, including term banks, paraphrase lists, parsers, named-entity recognizers, etc. With so many resources being continuously released and improved, it can be difficult to know which particular resource to use when developing a system.

In response, the Recognizing Textual Entailment (RTE) shared task community initiated a new activity for building this Textual Entailment Resource Pool. RTE participants and any other member of the NLP community are encouraged to contribute to the pool.

In an effort to determine the relative impact of the resources, RTE participants are strongly encouraged to report, whenever possible, the contribution to the overall performance of each utilized resource. Formal qualitative and quantitative results should be included in a separate section of the system report as well as posted on the talk pages of this Textual Entailment Resource Pool.

Adding a new resource is very easy. See how to use existing templates to do this in Help:Using Templates.